966 resultados para dynamic methods


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The national and Victorian burden of disease studies in Australia set out to examine critically the methods used in the Global Burden of Disease study to estimate the burden of mental disorders. The main differences include the use of a different set of disability weights allowing estimates in greater detail by level of severity, adjustments for comorbidity between mental disorders, a greater number of menta I disorders measured, and model ling of substance use disorders, anxiety disorders and bipolar disorder as chronic conditions. Uniform age-weighting in the Australian studies produces considerably lower estimates of the burden due to mental disorders in comparison with age-weighted disability-adjusted life years. A lack of follow-up data on people with mental disorders who are identified in cross-sectional surveys poses the greatest challenge in determining the burden of mental disorders more accurately.

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We shall be concerned with the problem of determining quasi-stationary distributions for Markovian models directly from their transition rates Q. We shall present simple conditions for a mu-invariant measure m for Q to be mu-invariant for the transition function, so that if m is finite, it can be normalized to produce a quasi-stationary distribution. (C) 2000 Elsevier Science Ltd. All rights reserved.

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The chondroitin sulfate proteoglycans neurocan and phosphacan are believed to modulate neurite outgrowth by binding to cell adhesion molecules, tenascin, and the differentiation factors heparin-binding growth-associated molecule and amphoterin. To assess the role of these chondroitin sulfate proteoglycans in the olfactory system, we describe here their expression patterns during both embryonic and postnatal development in the mouse. Immunoreactivity for neurocan was first detected in primary olfactory neurons at embryonic day 11.5 (E11.5). Neurocan was expressed by primary olfactory axons as they extended toward the rostral pole of the telencephalon as well as by their arbors in glomeruli after they contacted the olfactory bulb. The role of neurocan was examined by growing olfactory neurons on an extracellular matrix substrate containing neurocan or on extracellular matrix in the presence of soluble neurocan. In both cases, neurocan strongly promoted neurite outgrowth. These results suggest that neurocan supports the growth of primary olfactory axons through the extracellular matrix as they project to the olfactory bulb during development. Phosphacan, unlike neurocan, was present within the mesenchyme surrounding the E11.5 and E12.5 nasal cavity. This expression decreased at E13.5, concomitant with a transient appearance of phosphacan in nerve fascicles. Within the embryonic olfactory bulb, phosphacan was localised to the external and internal plexiform layers. However, during early postnatal development phosphacan was concentrated in the glomerular layer. These results suggest that phosphacan may play a role in delineating the pathway of growing olfactory axons as well as defining the laminar organization of the bulb. Together, the spatiotemporal expression patterns of neurocan and phosphacan indicate that these chondroitin sulfate proteoglycans have diverse in situ roles, which are dependent on context-specific interactions with extracellular and cell adhesion molecules within the developing olfactory nerve pathway. (C) 2000 Wiley-Liss, Inc.

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Early intervention for hazardous alcohol use has been shown repeatedly to be effective in reducing alcohol consumption, limiting alcohol-related problems and improving biochemical parameters. However, in most studies the follow-up period has been 2 years or less. The current paper presents progress on a 10-year follow-up of a randomized controlled trial of early intervention. Methods used for tracing subjects and ensuring minimal refusals are detailed. The intensity of effort required to locate subjects is documented and recommendations for ensuring good follow-up rates are made. At completion of follow-up, 72.5% of the sample reviewed here and 78.2% of the total cohort had been traced. Our experiences demonstrate that long-term follow-up is feasible, given sufficient planning and persistence.

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I noted with interest the article by Drs Perrin and Guex, entitled &dquo;Edema and leg volume: Methods of assessment,&dquo; published in Angiology 51:9-12, 2000. This was a timely and comprehensive review of the various methods in clinical use for the assessment of peripheral edema, notably in the leg. I would like to take this opportunity to alert readers to a further technique useful for this purpose, namely, bioelectrical impedance analysis. An early reportl described its use for the measurement of edema in the leg, but other than its successful use for the assessment of edema in the arm following masteCtoMy,2,1 the potential of the method remains to be fully realized. This is unfortunate since the method directly and quantifiably measures edema.

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Depending on the size and shape of the materials, methods employed to achieve effective fluidization during fluid bed drying varies from use of simple hole distributors for small, light weight materials to special techniques for lager and/or moist materials. This paper reviews common air distributors used in fluidized bed drying of food particulates. Also it reviews special methods of fluidizing larger irregular food particulates.

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I shall discuss the quantum and classical dynamics of a class of nonlinear Hamiltonian systems. The discussion will be restricted to systems with one degree of freedom. Such systems cannot exhibit chaos, unless the Hamiltonians are time dependent. Thus we shall consider systems with a potential function that has a higher than quadratic dependence on the position and, furthermore, we shall allow the potential function to be a periodic function of time. This is the simplest class of Hamiltonian system that can exhibit chaotic dynamics. I shall show how such systems can be realized in atom optics, where very cord atoms interact with optical dipole potentials of a far-off resonance laser. Such systems are ideal for quantum chaos studies as (i) the energy of the atom is small and action scales are of the order of Planck's constant, (ii) the systems are almost perfectly isolated from the decohering effects of the environment and (iii) optical methods enable exquisite time dependent control of the mechanical potentials seen by the atoms.

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A number of techniques have been developed to study the disposition of drugs in the head and, in particular, the role of the blood-brain barrier (BBB) in drug uptake. The techniques can be divided into three groups: in-vitro, in-vivo and in-situ. The most suitable method depends on the purpose(s) and requirements of the particular study being conducted. In-vitro techniques involve the isolation of cerebral endothelial cells so that direct investigations of these cells can be carried out. The most recent preparations are able to maintain structural and functional characteristics of the BBB by simultaneously culturing endothelial cells with astrocytic cells,The main advantages of the in-vitro methods are the elimination of anaesthetics and surgery. In-vivo methods consist of a diverse range of techniques and include the traditional Brain Uptake Index and indicator diffusion methods, as well as microdialysis and positron emission tomography. In-vivo methods maintain the cells and vasculature of an organ in their normal physiological states and anatomical position within the animal. However, the shortcomings include renal acid hepatic elimination of solutes as well as the inability to control blood flow. In-situ techniques, including the perfused head, are more technically demanding. However, these models have the ability to vary the composition and flow rate of the artificial perfusate. This review is intended as a guide for selecting the most appropriate method for studying drug uptake in the brain.

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The simultaneous design of the steady-state and dynamic performance of a process has the ability to satisfy much more demanding dynamic performance criteria than the design of dynamics only by the connection of a control system. A method for designing process dynamics based on the use of a linearised systems' eigenvalues has been developed. The eigenvalues are associated with system states using the unit perturbation spectral resolution (UPSR), characterising the dynamics of each state. The design method uses a homotopy approach to determine a final design which satisfies both steady-state and dynamic performance criteria. A highly interacting single stage forced circulation evaporator system, including control loops, was designed by this method with the goal of reducing the time taken for the liquid composition to reach steady-state. Initially the system was successfully redesigned to speed up the eigenvalue associated with the liquid composition state, but this did not result in an improved startup performance. Further analysis showed that the integral action of the composition controller was the source of the limiting eigenvalue. Design changes made to speed up this eigenvalue did result in an improved startup performance. The proposed approach provides a structured way to address the design-control interface, giving significant insight into the dynamic behaviour of the system such that a systematic design or redesign of an existing system can be undertaken with confidence.

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Tidal fluctuations in a leaky confined coastal aquifer are damped significantly due to leakage into an overlying phreatic aquifer. Jiao and Tang [1999] presented an analytical solution to a simple model describing this phenomenon. Their solution assumes that the tidal fluctuations in the overlying phreatic aquifer are negligible (i.e,, a static phreatic aquifer), Here we examine dynamic effects of the overlying aquifer based on a new approximate analytical solution. The numerical results indicate that the dynamic effects can be significant for a relatively large leakage and a high transmissivity of the phreatic aquifer.

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Realistic time frames in which management decisions are made often preclude the completion of the detailed analyses necessary for conservation planning. Under these circumstances, efficient alternatives may assist in approximating the results of more thorough studies that require extensive resources and time. We outline a set of concepts and formulas that may be used in lieu of detailed population viability analyses and habitat modeling exercises to estimate the protected areas required to provide desirable conservation outcomes for a suite of threatened plant species. We used expert judgment of parameters and assessment of a population size that results in a specified quasiextinction risk based on simple dynamic models The area required to support a population of this size is adjusted to take into account deterministic and stochastic human influences, including small-scale disturbance deterministic trends such as habitat loss, and changes in population density through processes such as predation and competition. We set targets for different disturbance regimes and geographic regions. We applied our methods to Banksia cuneata, Boronia keysii, and Parsonsia dorrigoensis, resulting in target areas for conservation of 1102, 733, and 1084 ha, respectively. These results provide guidance on target areas and priorities for conservation strategies.

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1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.

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Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

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Simulations provide a powerful means to help gain the understanding of crustal fault system physics required to progress towards the goal of earthquake forecasting. Cellular Automata are efficient enough to probe system dynamics but their simplifications render interpretations questionable. In contrast, sophisticated elasto-dynamic models yield more convincing results but are too computationally demanding to explore phase space. To help bridge this gap, we develop a simple 2D elastodynamic model of parallel fault systems. The model is discretised onto a triangular lattice and faults are specified as split nodes along horizontal rows in the lattice. A simple numerical approach is presented for calculating the forces at medium and split nodes such that general nonlinear frictional constitutive relations can be modeled along faults. Single and multi-fault simulation examples are presented using a nonlinear frictional relation that is slip and slip-rate dependent in order to illustrate the model.